In this project, I will perform simple exploratory data analysis of the FIFA 19 data set. The data set can be found on Kaggle. FIFA is the Fédération Internationale de Football Association and FIFA 19 is part of the FIFA series of association football video games. It is one of the best selling video games of all time selling over 260 million copies to date.
For this analysis we will be using the python pandas library, numpy, seaborn and matplotlib. The dataset contains 89 columns but we will limit our analysis to the following ten columns:
Name — Name of Player Age — Age of Player Nationality — Nationality of Player Value — Current Market Value Wage — Wage of Player Preferred Foot — Preferred foot of player Height — Height of Player Weight — Weight of player Position — Position on the pitch Overall — Player’s Overall Rating
- We've drawn many interesting conclusions from this dataset and analysis. Some of them are -
- There are 17981 players in Fifa 21.
- There are 162 different countries from where there are players in Fifa 21. Out of which there are 3 countries with more than 1000 players.
- There are 1496 players from England, 1138 players from Germany and 1055 players from Spain.
- There are around 713 clubs with each club having around 30 players.
- Maximum number of players falls in the age group 25 to 30.
- More than 1400 players are of the age 24.
- Highest overall rating in Fifa 21 is 94. Lionel Messi is the highest rated player with 94 overall rating